Mingyi Shi

45 papers receiving 1.1k citations

Peers

Mingyi Shi
Comparison fields: 5 of 85
  • Endocrine and Autonomic Systems 313
  • Cellular and Molecular Neuroscience 581
  • Pharmacology 171
  • Reproductive Medicine 70
  • Endocrinology, Diabetes and Metabolism 126
Replace Mei Yu with:
Mei Yu China
Tomi Streng Finland
W. Wallace Harrington United States
Neide Hyppolito Jurkiewicz Brazil
James E. Bowe United Kingdom
Prasad S. Dalvi United States
Kristie Conde United States
Tomohiro Higashi Japan
Karen Jesus Oliveira Brazil
Jianguo Niu China
Mingyi Shi relative to Mei Yu China Mei Yu's profile →
Citations per field
00.5×1.5×1.9×
Mei Yu · 1×
Citations per year

Countries citing papers authored by Mingyi Shi

Since Specialization
Citations

This map shows the geographic impact of Mingyi Shi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mingyi Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingyi Shi more than expected).

Fields of papers citing papers by Mingyi Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mingyi Shi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mingyi Shi. The network helps show where Mingyi Shi may publish in the future.

Co-authors

The 25 scholars most cited alongside Mingyi Shi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mingyi Shi Line = papers co-authored together Mingyi Shi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201265
2 201164
3 201760
4 201958
5 201252
6 201150
7 201148
8 201946
9 201243
10 201236
11 200932
12 201432
13 201132
14 201532
15 201828
16 201326
17 201524
18 201424
19 201823
20 201723

About Mingyi Shi

Mingyi Shi is a scholar working on Cellular and Molecular Neuroscience, Endocrine and Autonomic Systems, Surgery, Molecular Biology and Pharmacology, having authored 45 papers that have together received 1.1k indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (34 papers), Regulation of Appetite and Obesity (19 papers), Receptor Mechanisms and Signaling (11 papers), Cardiovascular, Neuropeptides, and Oxidative Stress Research (11 papers), Flavonoids in Medical Research (4 papers), Adipose Tissue and Metabolism (4 papers), Heavy metals in environment (3 papers) and Apelin-related biomedical research (3 papers). The work is most often cited by research in Endocrine and Autonomic Systems (313 citations), Cellular and Molecular Neuroscience (581 citations), Pharmacology (171 citations), Reproductive Medicine (70 citations) and Endocrinology, Diabetes and Metabolism (126 citations). Mingyi Shi has collaborated with scholars based in China, Iran and Sweden. Frequent co-authors include Penghua Fang, Zhenwen Zhang, Ping Bo, Mei Yu, Yan Zhu, Lili Guo, Biao He, Ling Zhang, Guangzhi Li and Bo Ping. Their work appears in journals such as Peptides, Experimental Gerontology, General and Comparative Endocrinology, Molecular and Cellular Endocrinology and Cellular Physiology and Biochemistry.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact